Сравнение методов

	Анализ политических сценариев	Стохастический сценарный анализ
Область	Имитационное моделирование	Имитационное моделирование
Семейство	Process / pipeline	Process / pipeline
Год появления	1967–1990s	1955–1980s
Автор метода	Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD	Dantzig, G. B.; Birge, J. R.; and others in stochastic programming tradition
Тип	Qualitative-quantitative hybrid scenario method	Probabilistic scenario enumeration and evaluation
Основополагающий источник	Swart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146.	Birge, J. R., Louveaux, F. (2011). Introduction to Stochastic Programming (2nd ed.). Springer. ISBN: 9781461402374
Другие названия	PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis	Probabilistic Scenario Analysis, SSA, Stochastic What-If Analysis, Monte Carlo Scenario Analysis
Связанные	5	4
Сводка	Policy Scenario Analysis is a structured method for evaluating how different policy interventions perform across a range of plausible future states. By pairing specific policy levers with alternative scenarios, analysts can assess robustness, trade-offs, and unintended consequences of policy choices before implementation — making it a cornerstone of evidence-based policy design in fields from climate to public health.	Stochastic Scenario Analysis evaluates a system or decision across multiple explicitly defined scenarios, each assigned a probability of occurrence. Unlike deterministic scenario analysis, it propagates uncertainty through probability distributions and computes expected outcomes, variance, and risk metrics across the scenario space, giving decision-makers a structured view of what could happen and how likely each outcome is.